1. Field of the Invention
The present invention relates generally to computerized information retrieval and more particularly is directed toward the ordering of lists of records returned in response to a set of search criteria.
2. Related Art
Website providers generally desire that their website search solution provide the best possible results because site search has been shown to have a conversion rate (i.e., the percentage of visitors who take a desired action) that is greater than that of overall site conversion rates. Accordingly, website providers understand that a satisfying site search experience for users will lead to increased sales, higher customer contentment, and lower customer service costs.
Characteristics that lead to successful site search solutions include: (1) Scope—Includes every page or product on the site(s); (2) Speed—Results are available immediately; (3) Currency—All information is completely up-to-date; (4) Recall—Finds every document and/or product that is relevant to the query; (5) Precision—No irrelevant pages or products are included in the results; and (6) Ranking—The most relevant results come first, less relevant results come later.
All six of these characteristics are handled well by conventional systems, but the hardest one to do well is ranking. Conventional methods use page information (title, body, metadata) and site architecture information to determine what pages should be shown in what order. At best, this information helps identify what the visitor wants to find; that is, the top slot on the first page of results is what the visitor wishes. At worst, it is only a loose correlation. For example, a product named “winter backpack” might be found lower in the results list than “backpack soap” when a visitor searched for “backpack”, mostly driven by the fact that the “backpack soap” product included the word “backpack” in the product description more often. This is true of all search engines, and while each has special enhancements to improve relevancy, all search algorithms may yet be improved, especially through the use of additional data sources beyond site content and architecture.
The most often provided enhancement supporting site search optimization is to give control to the customer by allowing them to incorporate tuning, such as with keywords, synonyms, target tags, direct hits, and more, to further guide what results show, and in which order they are shown. However, this process requires manual tuning and intervention, which is a laborious process.
Other conventional ranking methods include interrogating a website and using any information in the site to drive relevancy. In particular, data obtained in this way is not limited to data found in a product database. For example, a website may include both products (with pricing, title, description, and more) and supporting content such as press releases and product rewards. Additional conventional ranking methods may use other techniques including adjusting the weightings for standard document elements and adding new metadata for consideration by the ranking algorithms (e.g., a “rank” metatag).
What is yet needed, however, is an efficient and accurate system and method to better optimize search results automatically, thereby overcoming these significant problems found in the conventional systems as described above.